import numpy as np
import pandas as pd
import os
import sys
import pickle
from joblib import dump, load
import yaml
import statsmodels.api as sm
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
from sklearn.ensemble import RandomForestClassifier
from sklearn.model_selection import RandomizedSearchCV
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA
from sklearn.linear_model import LinearRegression as reg
import pdb
from pprint import pprint
from statistics import mean
import random
random.seed(50)
import math
import argparse

sys.path.insert(1,'/REDACTED/fairness/code/rf/scripts/rf')
#import tune_utils_alt_outcome as tu

###############################################
#### GET PLOT DICTIONARIES
###############################################

###############################################
### REFUNDABLE CREDIT REGRESSOR
###############################################

from gpd_test_alt_outcome import *
get_plot_dict_new(acsource='return',
                eitc=True,
                activity_code = None,
                rand_seed=50,
                bootstrap=False,
                bootstrap_iters=100,
                model='reg',
                retrain=True,
                thresh=None,
                dep_database=True,
                write_test=False,
                one_fold_params=False,
                fold_for_params=None,
                datapath='/REDACTED/fairness/code/rf/data/',
                outdir='/REDACTED/data/modeled_refactor_temp/costs_v2/net_rev/',
                outcome='ref_cred_amt_dif_pv',
                net_rev_version = True,
                config_to_use = 'original',
                costs_v2 = True)